class_docstr: ARLSTem stemmer : a light Arabic Stemming algorithm without any dictionary.
  Department of Telecommunication & Information Processing. USTHB University,
  Algiers, Algeria.
  ARLSTem.stem(token) returns the Arabic stem for the input token.
  The ARLSTem Stemmer requires that all tokens are encoded using Unicode
  encoding.
class_docstr_tok: ["ARLSTem","stemmer",":","a","light","Arabic","Stemming","algorithm","without","any","dictionary",".","Department","of","Telecommunication","&","Information","Processing",".","USTHB","University",",","Algiers",",","Algeria",".","ARLSTem.stem","(","token",")","returns","the","Arabic","stem","for","the","input","token",".","The","ARLSTem","Stemmer","requires","that","all","tokens","are","encoded","using","Unicode","encoding","."]
docstr: transform the word from the feminine form to the masculine form.
docstr_tok: ["transform","the","word","from","the","feminine","form","to","the","masculine","form","."]
code: def fem2masc(self, token):
      """
      transform the word from the feminine form to the masculine form.
      """
      if token.endswith("\u0629") and len(token) > 3:
          return token[:-1]
  
file_path: nltk/nltk/stem/arlstem.py
imports: import re
  from nltk.stem.api import StemmerI
label_desc: Use image node_id 6 for calling the ARLSTem obj's underlying member method code with example usage: obj.fem2masc(token) and returns: token